aais.com Strategic Scheduling for Student Success January 12, 2017 Laura Kelley, Senior Consultant Ad Astra Information Systems
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Strategic Scheduling for Student SuccessJanuary 12, 2017
Laura Kelley, Senior ConsultantAd Astra Information Systems
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Agenda• Context for Scheduling• Consulting Process• Higher Education Scheduling Index • System Metrics• What’s next?• Q&A
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Ad Astra Solutions PortfolioAstra Schedule™ – an enterprise class scheduling system that integrates with student information systems to optimize and analyze space utilization, create “what-if” scenario models, and manage rooms for classes, exams, events, and other resource scheduling. This robust tool also produces custom calendars and report to enhance visibility into campus scheduling.
Platinum Analytics™ – a patented, predictive course demand analysis system that assesses student course needs and suggests high-impact schedule changes to advance student program completion and operational efficiency. This analytics package is coupled with professional consulting to enhance application of the data.
Strategic Scheduling CheckUp™ – a customized institutional study and presentation of actionable data that baselines academic operation by analyzing instructional capacity and historical course offering trends. This engagement is an introduction to Ad Astra’s Higher Education Scheduling Index (HESI™) and includes an analysis of results with consultative guidance from industry experts, implementation support, and best practice recommendations.
HESI™ Dashboards - The HESI is the industry’s only peer comparison database of performance indicators for the allocation of faculty and academic space. The HESI Dashboards provide access to this database to benchmark your institution. Your data is refreshed once each major academic term and provides longitudinal tracking and insight to opportunities for balancing instructional resources.
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FOUR YEAR PRIVATE
COMMUNITY COLLEGE
FOUR YEAR PUBLIC
© 2015 AD ASTRA INFORMATION SYSTEMS™, L.L.C.
HIGHER EDUCATION SCHEDULING INDEX157 PEER INSTITUTIONS
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Typical Schedule Building Process
Typical Goal: Completion vs. Improvement
Course offerings are based on a historical schedule, typically a roll-forward of a “like” term
Departments refine offerings in silos. Distinct processes and
decision makers, limited collaboration and decision-
support tools
SIS is updatedRoom assignments are made/refined
“Final” schedule is posted Changes still occur after registration or even after
classes start
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THE SCHEDULE
IT IS COMPLEX!
© 2015 AD ASTRA INFORMATION SYSTEMS™, L.L.C.
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Consulting Process
1. Gather data• Section data - Banner• Room data – provided
by each institution
2. Initial Analysis• Ad Astra uses
proprietary software to build findings
3. Data Review• Meeting with institution
to review data• Establish standards and
data exclusions
4. Final Analysis• Finalize data• Perform final review call• Prepare for onsite visit
5. Consulting• On-site delivery• Mobilization meetings• Dashboard
6. Mobilization• Adjust Schedule• Track Progress• Repeat!
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ENROLLMENT RATIOAll HESI Database Schools
22
29
77%FILLED
To achieve the best allocation of faculty and instructional space, course enrollment should closely match course capacity. Our industry average is 77 percent. 2 year public average is 73%. 4 year public average is 81%.
Summer 2016 Higher Education Scheduling Index (HESI™)
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CLASSROOM SEAT FILL UTILIZATIONAll HESI Database Schools
22
34
65%FILLED
Summer 2016 Higher Education Scheduling Index (HESI™)
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CLASSROOMS UTILIZATION
All HESI Database Schools
STANDARD WEEK 46%
Summer 2016 Higher Education Scheduling Index (HESI™)
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SECTION ELIMINATION CANDIDATES, 7.0%
SECTIONS NEEDED BY STUDENT, 82.7%
SECTION REDUCTION CANDIDATES, 10.4%
Typical ScheduleAll HESI Database Schools
Summer 2016 Higher Education Scheduling Index (HESI™)
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What does the data tell us?• Most institutions have enough space to offer what is needed
― Is it the right type of space? What is the quality of the space?― Will students take courses outside of the perceived ‘prime-time’?― How do business practices impact space availability?
― Off grid scheduling― Very limited prime time
― How do you accommodate institutions that DO need additional space?
• Most institutions can benefit from schedule realignment― Only 5-10% of a normal schedule may need to be tweaked― Small changes can have big impacts― Consolidation of sections can help from a resource efficiency perspective and also allow
institutions to offer more ‘required’ courses― Monitoring the schedule activity closely is the only way to get better
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Course Offerings Metrics – Community CollegesGoal HESI CC
MeanHawai‘I
CC
Honolulu
CC
Kapi‘olani
CC
Kaua‘i
CC
Leeward
CC
UH Maui College
Windward
CC
Enrollment
Ratio85% 73% 75% 68% 88% 68% 89% 78% 79%
Enrollment N/A 18 17 17 21 14 20 19 18
Enrollment Cap N/A 24 22 24 24 21 22 24 22
Under-Utilized Course Ratio
<30% 38% 54% 55% 23% 56% 23% 43% 38%
Balanced Course Ratio
>60% 35% 31% 31% 49% 29% 47% 35% 40%
Overloaded Course Ratio
<10% 15% 15% 14% 28% 14% 30% 22% 22%
Reduction Candidates
5% 10% 7% 8% 3% 2% 4% 6% 4%
Elimination Candidates
3% 8% 6% 7% 1% 7% 1% 5% 4%
Addition Candidates, Analysis Term
5% 2% 1% 1% 1% 0% 0% 1% 1%
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Course Offerings Metrics – 4 year PublicGoal 4 -year
Public MeanUH Mānoa UH Hilo UH West
O‘ahu
EnrollmentRatio
85% 81% 77% 76% 80%
Enrollment N/A 26 21 22 20
Enrollment Cap N/A 32 27 29 26
Under-Utilized Course Ratio
<30% 36% 40% 38% 36%
Balanced Course Ratio
>60% 31% 35% 39% 31%
Overloaded Course Ratio
<10% 31% 23% 24% 32%
Reduction Candidates 5% 10% 8% 2% 2%
Elimination Candidates
3% 5% 4% 2% 5%
Addition Candidates, Analysis Term
5% 5% 2% 1% 3%
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Space Utilization (Capacity) Metrics – Community CollegesGoal HESI CC
MeanHawai‘I CC Honolulu
CCKapi‘olani
CCKaua‘i CC Leeward
CCUH Maui
College
WindwardCC
# Hours in Standard Week
N/A 66 65 68 74 61 58 61 84
# Hours in Prime Week(s) N/A 24 20 28 24 24 21 20 24
Classroom Utilization -Standard Week
50% 37% 35% 26% 43% 33% 40% 34% 24%
Classroom Utilization -Primetime
80% 49% 64% 50% 78% 53% 77% 55% 67%
Prime Ratio 50% 59% 56% 79% 59% 62% 71% 52% 80%
Seat Fill Utilization -Enrollment
75% 62% 62% 55% 73% 60% 72% 56% 64%
Seat Fill Utilization -Enrollment Cap
90% 84% 81% 88% 81% 82% 84% 80% 80%
Off-Grid
Utilization20% 48% 45% 64% 55% 44% 37% 42% 29%
Off-Grid Waste 5% 17% 16% 19% 12% 14% 9% 10% 4%
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Space Utilization (Capacity) Metrics – 4 year PublicGoal 4 -year Public
MeanUH Mānoa UH Hilo UH West
O‘ahu
# Hours in Standard Week
N/A 74 61 61 63
# Hours in Prime Week(s)
N/A 24 24 24 32
Classroom Utilization -Standard Week
50% 43% 48% 33% 58%
Classroom Utilization -Primetime
80% 78% 77% 53% 88%
Prime Ratio 50% 59% 64% 62% 78%Seat Fill Utilization -Enrollment
75% 73% 58% 60% 44%
Seat Fill Utilization -Enrollment Cap
90% 81% 98% 82% 61%
Off-GridUtilization
20% 55% 42% 44% 17%
Off-Grid Waste 5% 12% 12% 14% 3%
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Overall Strategy Recommendations
• Develop a schedule review team and process― Senior leadership and academic department representation― Focused on leveraging and sharing schedule analysis― Utilize the data and dashboards to impact the schedule
• Develop data-driven scheduling policies― Course offering efficiency and effectiveness― Meeting pattern and room assignment efficiency
• Consolidate data ― Astra has a standard Banner import that would facilitate data processing― Room data has no centralization of standardization across the system
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Course Offerings Recommendations• Consider efficiency candidates as schedules are built to determine where
changes can be made• Reduction candidates• Elimination candidates
• Consider addition candidates as schedules are built to determine how to address bottlenecks
• Historical analysis is not the ‘best’ way to find bottlenecks• Continue to partner on using GPS data
• Utilize the dashboards and final snapshot reports to review changes recommended/made
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Space Utilization (Capacity) Recommendations• UH West Oahu may need to consider additional space or updating the
existing larger space to create smaller ones• Several institutions have compact primetime offerings; Can some offerings be
spread outside this window• Space impact• Student conflict-free schedule impact
• Off-grid utilization and waste can impact how ‘full’ an institution feels; Can institutions adhere more closely to the agreed upon grid
• Space impact• Student conflict-free schedule impact
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Final Recommendation
• Resist inertia• All institutions are unique but similar; review the individual
findings and determine a strategy that works for your institution
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